4 citations · 6 across the 2 of their papers we have counts for
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cs.AI2018
AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias
Rachel K. E. Bellamy, Kuntal Dey, Michael Hind +15
Fairness is an increasingly important concern as machine learning models are used to support decision making in high-stakes applications such as mortgage lending, hiring, and priso…
stat.ML2018
Fairness GAN
Prasanna Sattigeri, Samuel C. Hoffman, Vijil Chenthamarakshan +1
In this paper, we introduce the Fairness GAN, an approach for generating a dataset that is plausibly similar to a given multimedia dataset, but is more fair with respect to protect…